The Nimbus repo contains code for inference of a machine learning model that classifies cells into marker positive/negative for arbitrary protein markers and different imaging platforms.
Create an environment with a Python version between 3.9-3.11 and install this package via pip install Nimbus-Inference, then download the template notebook from here 1_Nimbus_Predict.ipynb to get started.
See the changelog.
If you found a bug, please use the issue tracker. For questions and help requests, you can also reach out in the issue tracker.
@article{rum2024nimbus,
title={Automated classification of cellular expression in multiplexed imaging data with Nimbus},
author={Rumberger, J. Lorenz and Greenwald, Noah F. and Ranek, Jolene S. and Boonrat, Potchara and Walker, Cameron and Franzen, Jannik and Varra, Sricharan Reddy and Kong, Alex and Sowers, Cameron and Liu, Candace C. and Averbukh, Inna and Piyadasa, Hadeesha and Vanguri, Rami and Nederlof, Iris and Wang, Xuefei Julie and Van Valen, David and Kok, Marleen and Hollman, Travis J. and Kainmueller, Dagmar and Angelo, Michael},
journal={bioRxiv},
pages={2024--05},
year={2024},
publisher={Cold Spring Harbor Laboratory}
}